population genetic structure and gene flow in alcea
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Corresponding author: Li Pan, School of mechanical and electrical engineering, North China
institute of science & technology, Langfang City, Hebei Province, 065201, China
Email: hhxiaoxiaohh21@163.com; nasar.nas1990@gmail.com
UDC 575.630
https://doi.org/10.2298/GENSR2102867H Original scientific article
POPULATION GENETIC STRUCTURE AND GENE FLOW IN Alcea aucheri (BOISS.) ALEF.: A POTENTIAL MEDICINAL PLANT
Liu HANG1, Li PAN1,*, Tang YONG1, Luo JIANGUO1, Xu XINGMIN1, FAISAL2
1School of mechanical and electrical engineering, North China institute of science & technology,
(Hebei Key Laboratory of Safety Monitoring of Mining Equipment), Langfang City, Hebei
Province, 065201, China 2Institute of Plant Sciences, University of Sindh, Jamshoro, Pakistan.
Hang L., L. Pan, T. Yong, L. Jianguo, X. Xingmin, Faisal (2021). Population genetic
structure and gene flow in Alcea aucheri (boiss.) Alef.: a potential medicinal plant-
Genetika, Vol 53, No.2, 867-882.
The genus Alcea, a member of Malvaceae family consists of approximately 75 species
worldwide distributing mainly in South-West Asia. Among these, 33 species grow in Iran.
Plants of the Alcea (or Althaea) are among important medicinal plants in Iranian
traditional medicine. They have long been used in the treatment of health problems and
diseases. Alcea aucheri (Boiss.) Alef. species are distributed in different habitats of Iran.
There is no information on its population genetic structure, genetic diversity, and
morphological variability in Iran. Therefore, due to the importance of these plant species,
we performed a combination of morphological and molecular data for this species. For
this study, we used 118 randomly collected plants from 10 geographical populations in 5
provinces. AMOVA test revealed significant genetic difference among the studied
populations and also revealed that, 74% of total genetic variability was due to within
population diversity while, 26% was due to among population genetic differentiation.
Mantel test showed positive significant correlation between genetic distance and
geographical distance of the studied populations. Networking, STRUCTURE analyses
revealed some degree of gene flow among these populations.
Keyword: Alcea aucheri, Gene flow, Genetic differentiation, Inter Simple
Sequence Repeats (ISSR).
868 GENETIKA, Vol. 53, No2, 867-882 2021
INTRODUCTION
Genetic diversity is a basic component of biodiversity and its conservation is essential
for long term survival of any species in changing environments (MILLS and SCHWARTZ, 2005;
TOMASELLO et al., 2015). Among different populations, genetic diversity is non randomly
distributed and is affected by various factors such as geographic variations, breeding systems,
dispersal mechanisms, life span, etc. Change in environmental conditions often leads to variation
in genetic diversity levels among different populations and populations with low variability are
generally considered less adapted under adverse circumstances (FALK and HOLSINGER, 1991;
OLIVIERI et al., 2016). Most of the authors agree that genetic diversity is necessary to preserve
the long-term evolutionary potential of a species (FALK and HOLSINGER, 1991). In the last
decade, experimental and field investigations have demonstrated that habitat fragmentation and
population decline reduce the effective population size. In the same way, most geneticists
consider population size as an important factor for maintaining genetic variation (ELLEGREN and
GALTIER, 2016; TURCHETTO et al., 2016). This is very important in fragmented populations
because are more vulnerable due to the loss of allelic richness and increased population
differentiation by genetic drift (decreases heterozygosity and eventual fixation of alleles) and
inbreeding depression (increases homozygosity within populations; FRANKHAM, 2005).
Therefore, knowledge of the genetic variability and diversity within and among different
populations is crucial for their conservation and management (e.g. CIRES et al., 2012, 2013;
ESFANDANI-BOZCHALOYI et al., 2018a, 2018b, 2018c, 2018d).
The genus Alcea, a member of Malvaceae family consists of approximately 75 species
worldwide distributing mainly in South-West Asia. Among these, 33 species grow in Iran
(ESCOBAR et al., 2009) while 16 species are endemic to the country (PAKRAVAN, 2008).
Regarding Iran, there are only a few studies on the taxonomy of the genus, since the report of
Alcea in Flora Iranica (RIEDEL, 1976). However, because of the special geographical situation of
Iran, further species could be expected to occur (PAKRAVAN and GHAHREMAN, 2003). Given its
striking appearance and geometry, Alcea could be easily distinguished from other genera; the
flowers are either solitary or arranged in racemes or fascicles on an unbranched upright stem
rising to over 2 m at a fast rate. This genus is also characterized by having long notched petals
ranging in color from white and yellow to pink and purple. The leaves usually appear on long
petioles and are often lobed or toothed, and adorn the whole parts of the herbage (AZIZOV et al.,
2007). From an industrial and medicinal point of view, Alcea is among the most important
genera recognized in the family Malvaceae. Molecular-phylogenetic data also support the
monophyly and distinctness (as suggested by morphological data) of Alcea but they are of
limited use in determining relationships between species and species delimitations (ESCOBAR et
al., 2012). Alcea exhibits a considerable taxonomic complexity (ZOHARY, 1963a,b; RIEDL, 1976;
TOWNSEND, 1980).
Alcea aucheri (Boiss.) Alef. is a perennial plant with 30 to 50 cm height, covered by
high densely hairs and dingy appearance. Flowers are pink, whity-pink or dingy pink and appear
among June and July, last up to first severe cold in autumn. The plant with acceptable
appearance and low water requirement could be a good choice to use in xeriscaping in arid and
semiarid regions. Its seed germination is inherently poor and becomes unpredictable, especially
in semi-arid regions characterized by low rainfall (SHAHEEN et al., 2010).
L. HANG et al.: GENETIC STRUCTURE IN Alcea aucheri 869
Plants of the Alcea (or Althaea) genus from Malvaceae family are among important
medicinal plants in Iranian traditional medicine. They have long been used in the treatment of
health problems and diseases. The flowers of Alcea spp. have been widely used as mucilage for
treatment of irritated oral and pharyngeal mucosa, respiratory, and gastrointestinal disorders, as
well as urinary complaints and skin inflammations. They have been also used as a diuretic agent
and sedative remedy (BLUMENTHAL et al., 2000). Some of species of the Alcea genus with
medicinal activities include Alcea rosea L. (hollyhock), A. officinalis L. (marshmallow), and A.
aucheri (Boiss.) Alef. (South marshmallow) (BLUMENTHAL et al., 2000).
Molecular markers play a significant role in protection of biodiversity, identification of
promising cultivars, quantitative trait loci (QTL) mapping, etc. Different PCR based dominant
markers such as ISSR, SCoT, SRAP, etc. have been effectively used for quantification of genetic
diversity (GEORGE et al., 2006). Recent ISSR studies of natural populations have demonstrated
the hypervariable nature of these markers and their potential use for population-level studies
(HULTE´N and FRIES, 1986). Limitations of the ISSR technique, as is the case for Random
Amplification of Polymorphic DNA (RAPD; (ESFANDANI-BOZCHALOYI et al., 2019), are that
bands are scored as dominant markers and that genetic diversity estimates are based on diallelic
characters. In the present study, ISSR markers were employed to analyze genetic diversity in 118
Alcea aucheri accessions belonging to 10 different populations for the first time in the Iran.
MATERIALS AND METHODS
Plant materials
A total of 118 individuals were sampled representing 10 natural populations of Alcea
aucheri in Kermanshah, Esfahan, Tehran, Fars, Yazd and Kerman Provinces of Iran during
July-Agust 2019-2020 (Table 1).
Table 1. Voucher details and diversity within Iranian populations of A. aucheri in this study
For morphometric and ISSR analysis we used 118 plant accessions (four to twelve
samples from each populations) belonging to 10 different populations with different eco-
geographic characteristics were sampled and stored in -20 till further use. More information
about geographical distribution of accessions are in Table 1 and Fig. 1. The specimens were
No Subspecies Locality Latitude Longitude Altitude (m)
Pop1 var. aucheri Boiss. Esfahan:Ghameshlou, Sanjab 36 ˚ 52'37 ̎ 52 ˚ 23' 92 ̎ 122
Pop2 var. aucheri Boiss. Tehran, Damavand 37°50̍ʹ03ʺ 49°24ʹ28ʺ -6
Pop3 var. aucheri Boiss. Fars, Estahban 36◦20ʹ07̎ʺ 50° 52ʹ08ʺ 13
Pop4 var. aucheri Boiss. Kermanshah, Islamabad 36 ˚ 52'373 54 ˚ 23' 92 ̎ 155
Pop5 var. aucheri Boiss. Tehran, Karaj, Malard 36° 57ʹ12ʺ 53° 57ʹ32ʺ 5
Pop6 var. lobata Bornm. Esfahan:Najafabad 36 ˚ 52'373 51 ˚ 23' 92 ̎ 180
Pop7 var. lobata Bornm. Yazd: Khormiz, 5km SW of
Mehriz, NE of Kuh-e Khoseh.
31 ˚ 52'373 54 ˚ 23' 92 ̎ 1700
Pop8 var. lobata Bornm. Fars, Darab 36°50ʹ03ʺ 53°24ʹ28ʺ -3
Pop9 var. lobata Bornm. Fars, Shiraz 36°14ʹ14ʺ 52°18ʹ07ʺ -14
Pop10 var. lobata Bornm. Kerman , Bam 36◦36ʹ93ʺ 52°27ʹ90ʺ 44
870 GENETIKA, Vol. 53, No2, 867-882 2021
identified using the identification keys and descriptions of the Alcea species in the relevant
floras [Taxonomical Studies in Alcea of South-western Asia (ZOHARY, 1963a, b), Flora
Orientalis (BOISSIER, 1967), Flora Palestina (ZOHARY, 1972), Flora Iranica (RIEDL, 1976), Flora
of Iraq (TOWNSEND et al., 1980). Vouchers were deposited at the herbarium of Islamic Azad
University, Science and Research Branch, Tehran, Iran (IAUH).
Fig. 1. Distribution map of the studied populations.
DNA extraction and ISSR assay
Fresh leaves were used randomly from four to twelve plants in each of the studied
populations. These were dried by silica gel powder. CTAB activated charcoal protocol was used
to extract genomic DNA (ESFANDANI-BOZCHALOYI et al., 2019). The quality of extracted DNA
was examined by running on 0.8% agarose gel. 10 ISSR primers; (AGC)5GT, (CA)7GT,
(AGC)5GG, UBC810, (CA)7AT, (GA)9C, UBC807, UBC811, (GA)9T and (GT)7CA
commercialized by UBC (the University of British Columbia) were used. PCR reactions were
carried in a 25μl volume containing 10 mM Tris-HCl buffer at pH 8; 50 mM KCl; 1.5 mM
MgCl2; 0.2 mM of each dNTP (Bioron, Germany); 0.2 μM of a single primer; 20 ng genomic
DNA and 3 U of Taq DNA polymerase (Bioron, Germany). The thermal program was carried
out with an initial denaturation for 1 min at 94°C, followed by 40 cycles in three segments: 35 s
at 95°C, 40s at 47°C and 55s at 72°C. Final extension was performed at 72°C for 5 min. The
amplification products were observed by running on 1% agarose gel, followed by the ethidium
L. HANG et al.: GENETIC STRUCTURE IN Alcea aucheri 871
bromide staining. The fragment size was estimated by using a 100 bp molecular size ladder
(Fermentas, Germany).
Data analyses
Morphological studies
In total 29 morphological quantitative characters were studied. Four to twelve samples
from each population were randomly studied for morphological analyses (Appendix 1).
Morphological characters were first standardized (Mean = 0, Variance = 1) and used to establish
Euclidean distance among pairs of taxa (PODANI, 2000). For grouping of the plant specimens,
The UPGMA (Unweighted paired group using average) and Ward (Minimum spherical
characters) as well as ordination methods of MDS (Multidimensional scaling) were used
(PODANI, 2000). PAST version 2.17 (HAMMER et al., 2012) was used for multivariate statistical
analyses of morphological data.
Molecular analyses
The ISSR profiles obtained for each samples were scored as binary characters.
Parameter like Nei’s gene diversity (H), Shannon information index (I), number of effective
alleles, and percentage of polymorphism (P% = number of polymorphic loci/number of total loci)
were determined (WEISING et al., 2005; FREELAND et al., 2011).
Shannon’s index was calculated by the formula: H’ = -Σpiln pi. Rp is defined per primer
as: Rp = ∑ Ib, were “Ib” is the band informativeness, that takes the values of 1-(2x [0.5-p]),
being “p” the proportion of each genotype containing the band. The percentage of polymorphic
loci, the mean loci by accession and by population, UHe, H’ and PCA were calculated by
GenAlEx 6.4 software (PEAKALL and SMOUSE, 2006)
Nei’s genetic distance among populations was used for Neighbor Joining (NJ)
clustering and Neighbor-Net networking (FREELAND et al., 2011; HUSON and BRYANT, 2006).
Mantel test checked the correlation between geographical and genetic distances of the studied
populations (PODANI, 2000). These analyses were done by PAST ver. 2.17 (HAMMER et al.,
2012), DARwin ver. 5 (2012) and SplitsTree4 V4.13.1 (2013) software.
AMOVA (Analysis of molecular variance) test (with 1000 permutations) as
implemented in GenAlex 6.4 (PEAKALL and SMOUSE, 2006), and Nei,s Gst analysis as
implemented in GenoDive ver.2 (2013) (MEIRMANS and VAN TIENDEREN, 2004) were used to
show genetic difference of the populations. Moreover, populations, genetic differentiation was
studied by G'ST est = standardized measure of genetic differentiation (HEDRICK, 2005), and
D_est = Jost measure of differentiation (JOST, 2008).
The clustering method based on the Bayesian-model implemented in the software
program STRUCTURE (PRITCHARD et al., 2000) was used on the same data set to better detect
population substructures. This clustering method is based on an algorithm that assigns genotypes
to homogeneous groups, given a number of clusters (K) and assuming Hardy-Weinberg and
linkage equilibrium within clusters, the software estimates allele frequencies in each cluster and
population memberships for every individual (PRITCHARD et al., 2000). The number of potential
subpopulations varied from two to ten, and their contribution to the genotypes of the accessions
was calculated based on 50,000 iteration burn-ins and 100,000 iteration sampling periods. The
872 GENETIKA, Vol. 53, No2, 867-882 2021
most probable number (K) of subpopulations was identified following EVANNO et al. (2005). In
K-Means clustering, two summary statistics, pseudo-F, and Bayesian Information Criterion
(BIC), provide the best fit for k (MEIRMANS, 2012).
Gene flow (Nm) which were calculated using POPGENE (version 1.31) program (YEH
et al., 1999). Gene flow was estimated indirectly using the formula: Nm = 0.25(1 - FST)/FST. In
order to test for a correlation between pair-wise genetic distances (FST) and geographical
distances (in km) between populations, a Mantel test was performed using Tools for Population
Genetic Analysis (TFPGA; MILLER, 1997) (computing 999 permutations). This approach
considers equal amount of gene flow among all populations. (ii) Population assignment test
based on maximum likelihood as performed in GenoDive ver. 2. (2013). The presence of shared
alleles was determined by drawing the reticulogram network based on the least square method by
DARwin ver 5. (2012).
RESULTS
Populations, genetic diversity
Genetic diversity parameters determined in 10 geographical populations of Alcea
aucheri populations are presented in Table 2. The highest value of percentage polymorphism
(45.38%) was observed in Fars, Shiraz (population No.9) which shows high value for gene
diversity (0.27). and Shanon, information index (0.33). Population Tehran, Damavand (No.2) has
the lowest value for percentage of polymorphism (18.82%) and the lowest value for Shanon,
information index (0.10), and He (0.070).
Table 2. Genetic diversity parameters in the studied populations Alcea aucheri
Pop N Na Ne I He UHe %P
Pop1 10 0.835 1.206 0.179 0.119 0.132 35.12
Pop2 14 0.541 1.118 0.104 0.070 0.084 18.82
Pop3 8 0.718 1.162 0.147 0.097 0.106 29.41
Pop4 15 0.918 1.225 0.197 0.132 0.159 35.29
Pop5 10 0.452 1.089 0.23 0.22 0.15 35.05%
Pop6 14 0.333 1.006 0.122 0.12 0.22 43.23%
Pop7 8 1.247 1.35 0.271 0.184 0.192 35.91%
Pop8 15 0.258 1.017 0.174 0.11 0.12 34.30%
Pop9 14 0.258 1.029 0.331 0.27 0.29 45.38%
Pop10 11 0.452 1.089 0.18 0.22 0.25 42.05%
N = number of samples, Na = No. of Different Alleles, Ne = No. of Effective Alleles = 1 / (p^2 + q^2)
I = Shannon's Information Index = -1* (p * Ln (p) + q * Ln(q)), He = Expected Heterozygosity = 2 * p * q
UHe = Unbiased Expected Heterozygosity = (2N / (2N-1)) * He, P%= percentage of polymorphism, populations
Where for Diploid Binary data and assuming Hardy-Weinberg Equilibrium, q = (1 - Band Freq.)^0.5 and p = 1 - q.
UHe = Unbiased Expected Heterozygosity = (2N / (2N-1)) * He
Where for Diploid Binary data and assuming Hardy-Weinberg Equilibrium, q = (1 - Band Freq.)^0.5 and p = 1 - q.
L. HANG et al.: GENETIC STRUCTURE IN Alcea aucheri 873
Population genetic differentiation
AMOVA (PhiPT = 0.356, P = 0.010), revealed significant difference among the studied
populations (Table 3). It also revealed that, 74% of total genetic variability was due to within
population diversity and 26% was due to among population genetic differentiation.
Table 3. Analysis of molecular variance (AMOVA) of the studied species. Source df SS MS Est. Var. % ΦPT
Among Pops 20 416.576 35.327 5.082 26% 26%
Within Pops 62 444.767 7.530 7.530 74%
Total 82 831.342 12.543 100%
The pairwise comparisons of ‘Nei genetic identity’ among the studied populations
Alcea aucheri (Table 4) have shown a higher a genetic similarity (0.89) between populations
Tehran, Damavand (pop. No 2) and Fars, Estahban (pop. No 3), while the lowest genetic
similarity value (0.65) occurs between Esfahan: Najafabad (pop. No.6) and Fars, Shiraz
populations (pop. No. 9).
Table 4. Pairwise Population Matrix of Nei Unbiased Genetic Identity
pop1 pop2 pop3 pop4 pop5 pop6 pop7 pop8 pop9 pop10
1.000 pop1
0.745 1.000 pop2
0.707 0.897 1.000 pop3
0.757 0.866 0.797 1.000 pop4
0.837 0.772 0.804 0.752 1.000 pop5
0.731 0.716 0.781 0.727 0.824 1.000 pop6
0.756 0.725 0.768 0.719 0.806 0.772 1.000 pop7
0.768 0.863 0.800 0.760 0.836 0.755 0.831 1.000 pop8
0.765 0.769 0.812 0.736 0.783 0.650 0.826 0.797 1.000 pop9
0.755 0.849 0.823 0.744 0.781 0.727 0.772 0.732 0.873 1.000 pop10
df: degree of freedom; SS: sum of squared observations; MS: mean of squared observations;
EV: estimated variance; ΦPT: proportion of the total genetic variance among individuals within an accession, (P < 0.001).
Stat Value P(rand >= data)
PhiPT 0.793 0.010
Probability, P(rand>=data), for PhiPT is based on permutation across the full data set.
PhiPT = AP / (WP + AP) = AP / TOT
Key: AP = Est. Var. Among Pops, WP = Est. Var. Within Pops
874 GENETIKA, Vol. 53, No2, 867-882 2021
Populations, genetic affinity
NJ tree and Neighbor-Net network produced similar results therefore only Neighbor-
Net network is presented and discussed (Figure. 2). We have almost complete separation of the
studied population in the network, supporting AMOVA result. The populations Yazd: Khormiz,
5km SW of Mehriz, NE of Kuh-e Khoseh (pop. No 7) and Fars, Darab; Fars, shiraz and Kerman,
Bam (pop. No 8,9,10) (A. aucheri var. lobate) are distinct and stand separate from the other
populations with great distance. The populations 1 and 2, as well as populations 3 and 5 (A.
aucheri var. aucheri) show closer genetic affinity and are placed close to each other. In general,
the description here about Figure 2 is more or less consistent with Figure 3.
Genetic divergence and separation of populations 1-5, as well as 6 - 10 from the other
populations is evident in MDS plot of ISSR data after 900 permutations (Figure.3). The other
populations showed close genetic affinity. Mantel test after 5000 permutations produced
significant correlation between genetic distance and geographical distance in these populations (r
= 0.987, P = 0.001). Therefore, the populations that are geographically more distant have less
amount of gene flow, and we have isolation by distance (IBD) in Alcea aucheri.
Fig.2. Neighbor-Net network of populations in Alcea aucheri based on ISSR data.
L. HANG et al.: GENETIC STRUCTURE IN Alcea aucheri 875
Fig. 3. MDS plot of populations in Alcea aucheri based on ISSR data.
Populations genetic structure
K = 2 reveal the presence of 2 genetic group. Similar result was obtained by Evanno test
performed on STRUCTURE analysis which produced a major peak at k = 2 (Figure.4, Table 5).
Both these analyses revealed that Alcea aucheri populations show genetic stratification.
Fig. 4. Delta k plot of Evanno’s test based on STRUCTURE analysis.
876 GENETIKA, Vol. 53, No2, 867-882 2021
Table 5. K-Means clustering result. (* Best clustering according to Calinski and Harabasz’ pseudo-F: k =
2. Best clustering according to Bayesian Information Criterion: k = 6).
k SSD(T) SSD(AC) SSD(WC) r-squared pseudo-F AIC BIC Rho
1 1119.354 0 0 0 0 216.38 580.088 0
2* 1119.354 545.8 573.5 0.488 10.061 177.47 556.102 0.472
3 1119.354 210.5 908.9 0.188 9.147 203.56 571.822 0.263
4 1119.354 292.3 827.1 0.261 9.189 198.04 568.493 0.303
5 1119.354 367.5 751.9 0.328 9.409 192.49 565.084 0.363
6 1119.354 438.8 680.5 0.392 9.801 186.65 561.316 0.4
7 1119.354 498.3 621 0.445 10.03 181.54 558.22 0.436
8 1119.354 697.1 422.3 0.623 9.493 165.74 553.028 0.576
9 1119.354 581 538.4 0.519 9.846 174.81 555.325 0.496
10& 1119.354 719.8 399.5 0.643 9.425 164.12 552.895 0.592
* Best clustering according to Calinski & Harabasz' pseudo-F: k = 2
& Best clustering according to Bayesian Information Criterion: k = 10
Fig. 5. Reticulogram of Alcea aucheri populations based on least square method analysis of ISSR data.
(Population numbers are according to Table 1.
STRUCTURE plot based on k = 2 (Figure 1, Table 5), revealed genetic affinity between
populations 1-5 (similarly colored), as well as populations 6-10.
The mean Nm = 0.354 was obtained for all ISSR loci, which indicates low amount of
gene flow among the populations and supports genetic stratification as indicated by K-Means
and STRUCTURE analyses. However, reticulogram obtained based on the least square method
L. HANG et al.: GENETIC STRUCTURE IN Alcea aucheri 877
(Figure. 5), revealed some amount of shared alleles among populations 10 and 7, and between 9
and 1-4. This result is in conflict with grouping we obtained with MDS plot, as these populations
were placed close to each other. As evidenced by STRUCTURE plot based on admixture model,
these shared alleles comprise very limited part of the genomes in these populations and all these
results are not in agreement in showing high degree of genetic stratification within Alcea aucheri
populations.
Morphometric analyses
In present study we used 118 plant accessions (four to twelve samples from each
populations) belonging to 10 different populations. PCA plot of Alcea aucheri populations based
on morphological characters produced similar results (Figure. 6). The result showed
morphological difference/ divergence among most of the studied populations. This
morphological difference was due to quantitative characters only. For example, character
(Number of segment stem leaves (mm) and shape basal leaves and stem leaves, separated
population No. 7-10, character (Width of basal leaves) separated population No. 1,3,4, while
character Calyx width, separated populations 2 and 5-6 from the other populations.
A consensus tree was obtained for both ISSR and morphological trees (Figure not
included), to reveal the populations that are diverged based on both morphological and molecular
features. Interesting enough, it showed divergence of almost all populations at molecular level as
well as morphological characteristics.
Fig. 6. PCA plot of Alcea aucheri populations based on morphological characters.
DISCUSSION
A well-suited system for investigating radiations in the Irano-Turanian region is the
genus Alcea L. (Malvaceae). It includes approximately 50 species, which are mainly of Irano-
Turanian distribution with extensions into the Caucasus and the eastern Mediterranean (ZOHARY,
1963b). Alcea comprises mostly tall-growing hemicryptophytes with simple, lobed,
878 GENETIKA, Vol. 53, No2, 867-882 2021
palmatipartite or palmatisect leaves with a more or less pronounced indumentum of stellate and
fasciculate hairs. Alcea is considered one of the most complicated and challenging genera of the
Middle Eastern flora (ZOHARY, 1963b; RIEDL, 1976; TOWNSEND, 1980; PAKRAVAN, 2001).
The present study revealed interesting data about its genetic variability, genetic
stratification and morphological divergence in south and west part of Iran. The studied
populations have a low level of genetic diversity (He = 0.034- 0.199). The Genetic diversity is of
fundamental importance in the continuity of a species as it is used to bring about the necessary
adaptation to the cope with changes in the environment (GUITTONNEAU, 1972). Degree of genetic
variability within a species is highly correlated with its reproductive mode, the higher degree of
open pollination/ cross breeding brings about higher level of genetic variability in the studied
taxon (KNUTH, 1908).
Low genetic variability may also occur due to small size of the populations and genetic
drift (DAHLGREN, 1980). These species tend to perform inbreeding as also evidenced by very low
Nm value and IBD obtained for the studied species. However, limited gene flow was not solely
due to geographical distance among the species, but some of the species, which grew in adjacent
areas with overlapping zones, did not form any hybrids or intermediate forms as evidenced by
morphological and ISSR clusters obtained (WEBB and CHATER, 1968).
In our study, 10 primer combinations could amplify 98 discrete bands of which 90 were
polymorphic (95% polymorphism). This value appeared to be relatively high, similar to the other
ISSR based studies, e.g. orchid (80.52%; CAI et al., 2011), Salvia miltiorrhiza (90%; SONG et al.,
2010), and coffee species (93%; MISHRA et al., 2011). This result implies that ISSR markers are
efficient for analyzing polymorphism level in Alcea. Occurrence of high polymorphism could be
explained for species in different climatic zones with varying selection pressure during the
course of evolution (MISHRA et al., 2011). Genetic diversity is affected by a number of
evolutionary factors including mating system, gene flow and seed dispersal, geographic range, as
well as natural selection (HAMRICK and GODT, 1989). The geographic range of species appears to
influence the levels of genetic diversity greatly. Generally, small geographic range of species
leads to less genetic diversity than geographically widespread species (HAMRICK and GODT,
1989). Based on this assumption, a high level of genetic diversity within species is expected in
Alcea. Our genetic similarity analysis revealed a wide degree of variation from 0.17 to 0.68,
which reflects sufficient amount of diversity among Alcea species in Iran.
According to BADRKHANI et al. (2014) sequence-related amplified polymorphism
(SRAP) marker was employed to assess the genetic diversity and genetic similarity relationships
among14 species of Alcea collected from northwest of Iran. Seventeen SRAP primer
combinations generated 104 fragments, of which 97 (93%) were polymorphic, with an average
of 5.7 polymorphic fragments per primer. Percentage of polymorphism ranged from 50% (ME2-
EM6) to a maximum of 100%, and mean polymorphism information content value obtained was
0.3. The lowest genetic similarity (0.17) was observed between A. sophiae and A. flavovirens,
while the highest was found between A. digitata and A. longipedicellata (0.68). Two main
clusters were detected using UPGMA, which did not correspond to geographical origin of the
species. Their study indicates that SRAP markers could be good candidates for assessing genetic
variation in Alcea.
L. HANG et al.: GENETIC STRUCTURE IN Alcea aucheri 879
Iranian Alcea species have only been characterized with morphological data, so far.
However, the genus has a complicated taxonomy due to small number of characters. Based on
study of PAKRAVAN (2008) on Alcea, only examination of the leaf sequence and configuration of
the carpels would represent valuable characters. For example, A. flavovirens and A. glabrata
differ only in the size of the carpel and width of wing (PAKRAVAN, 2008).
ESCOBAR et al. (2012) with using three molecular markers (nrDNA ITS and the plastid
spacers psbA-trnH and trnL-trnF), showed that a phylogeny of Alcea and test previous
infrageneric taxonomic hypotheses as well as its monophyly with respect to Althaea, a genus
with which it has often been merged. They additionally discuss morphological variation and the
utility of morphological characters as predictors of phylogenetic relationships. Their results show
that while molecular data unambiguously support the circumscription of Alcea inferred from
morphology, they prove to be of limited utility in resolving interspecific relationships,
suggesting that Alcea’s high species diversity is due to rapid and recent radiation. Their work
provides the first phylogeny of Alcea and aims to set the scene for the study of processes
underlying species radiation in the Irano-Turanian region.
Alcea aucheri is of wide spread in our country and it has several medicinal applications
(SHAHEEN et al., 2010), however we had no information on its genetic structure and detailed
taxonomic information. Our results revealed interesting data about its genetic variability, genetic
stratification and morphological divergence in south and west part of Iran.
ACKNOWLEDGMENT
Funding project of basic scientific research business of Central Universities (No. 3142019016,
No. 3142019055), Langfang City science and technology research and development plan self-
financing project (No. 2019011040), National innovation and entrepreneurship training program
for college students (No. 202011104012).
Received, March 13th, 2020
Accepted January 22nd, 2021
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GENETIČKA STRUKTURA POPULACIJE I PROTOK GENA KOD Alcea aucheri
(BOISS.) ALEF.: POTENCIJALNA LEKOVITA BILJKA
Liu HANG1, Li PAN1,*, Tang YONG1, Luo JIANGUO1, Xu XINGMIN1, FAISAL 2
1Škola za mehaničko i električno inžinjerstvo, Severnokineski institute za nauku i tehnologiju,
Langfang, Hebei provincija, 065201, Kina 2Institut za biljne nauke, Univerzitet Sindh, Jamshoro, Pakistan
Izvod
Rod Alcea, član familije Malvaceae, sastoji se od približno 75 vrsta širom sveta koje su
raspoređene uglavnom u jugozapadnoj Aziji. Među njima, 33 vrste rastu u Iranu. Biljke Alcee (ili
Althee) spadaju među važne lekovite biljke u iranskoj tradicionalnoj medicini. Dugo se koriste u
lečenju zdravstvenih problema i bolesti. Alcea aucheri (Boiss.) Alef. vrste su rasprostranjene u
različitim staništima Irana. Nema podataka o genetskoj strukturi njegove populacije, genetskoj
raznolikosti i morfološkoj varijabilnosti u Iranu. Zbog toga smo zbog važnosti ovih biljnih vrsta
izvršili kombinaciju morfoloških i molekularnih podataka za ovu vrstu. Za ovu studiju koristili
smo 118 nasumično prikupljenih biljaka iz 10 geografskih populacija u 5 provincija. AMOVA
test otkrio je značajnu genetsku razliku među proučavanim populacijama, a takođe je otkrio da je
74% ukupne genetske varijabilnosti bilo posledica populacione raznolikosti, dok je 26% bilo
genetičke diferencijacije populacije. Mantel test je pokazao pozitivnu značajnu korelaciju
između genetske udaljenosti i geografske udaljenosti proučavanih populacija. Umrežavanjem,
analize STRUKTURE otkrile su određeni stepen protoka gena među ovim populacijama.
Primljeno 13.III.2020.
Odobreno 22.I 2021.
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